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Phylogenetics, zoogeography, and the role of dispersal and vicariance in the evolution of the Rana catesbeiana (Anura: Ranidae) species group

2003· article· en· W1904991637 on OpenAlexaff
James D. Austin, Stephen C. Lougheed, Paul E. Moler, Peter T. Boag

Bibliographic record

VenueBiological Journal of the Linnean Society · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsQueen's University
Fundersnot available
KeywordsParaphylyBiologyVicarianceBiological dispersalZoogeographyBiogeographyPhylogenetic treeMolecular clockEcologyAllopatric speciationZoologyEvolutionary biologyPhylogeographyCladeGeneticsPopulation

Abstract

fetched live from OpenAlex

The Rana catesbeiana species group consists of seven species, each variously distributed across eastern North America. We estimated the evolutionary relationships among 31 exemplars and used the phylogenetic hypothesis to examine the potential modes of speciation and relative role of dispersal in the evolution and zoogeography of this species group. Phylogenetic relationships based on 1554 combined base pairs of the cytochrome b and ND2 mitochondrial genes suggest that the species are closely related, having undergone rapid radiation from a common ancestor during the late Miocene or Pliocene. A Pleistocene origin for the rare R. okaloosae is suggested by its pattern of paraphyly with R. clamitans and by its geographically restricted distribution, although hybridization as the explanation for paraphyly cannot be ruled out. Dispersal–vicariance analysis suggested a Coastal Plain biogeographical region origin of the species group, supporting the notion that the region was an important centre of anuran diversification, with post-speciation dispersal playing a major role in explaining the distribution of the widespread species, R. catesbeiana, R. clamitans, and R. septentrionalis. High sea levels during the late Tertiary, greatly reducing and insularizing parts of the southern Coastal Plain region may have played a major role in the diversification of this group.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.178
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2003
Admission routes1
Has abstractyes

Explore more

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